Impacts of pain on brain health explored using neuroimaging techniques: implications for patient treatment Emma Duerden, M...
Outline <ul><li>Introduction </li></ul><ul><ul><li>background </li></ul></ul><ul><li>Pain processing regions </li></ul><ul...
Introduction <ul><li>Pain:  </li></ul><ul><ul><li>Unpleasant sensory and emotional experience </li></ul></ul><ul><ul><li>A...
Introduction <ul><li>Pain:  </li></ul><ul><li>Statistics Canada 2001 </li></ul><ul><ul><li>1.5 million persons aged 15 to ...
Introduction <ul><li>Pain = psychological experience </li></ul><ul><li>No objective measures </li></ul><ul><li>Sensory and...
Peripheral mechanisms  of pain
Central mechanisms of pain
Introduction <ul><li>Neural processing of painful stimuli </li></ul><ul><li>Broad network of interconnected cortical regio...
Introduction <ul><li>Discriminative processing of pain  </li></ul><ul><ul><li>Lateral pain system </li></ul></ul><ul><ul><...
Introduction <ul><li>Affective (unpleasantness) processing of pain  </li></ul><ul><ul><li>Medial pain system </li></ul></u...
Brain imaging methods Laboratory of Neuro Imaging (LONI) at UCLA (http://www.loni.ucla.edu/)
http://www.fmrib.ox.ac.uk
Brain activity during pain <ul><ul><li>Positron emission tomography </li></ul></ul>
Brain activity during pain
Brain activity during pain
Brain activity during pain Rainville  et al. ,  M édecine Science  16  (2000) Thalamus S1 S2 Insula ACC
Why do a meta-analysis? <ul><ul><li>Contiguous activation </li></ul></ul><ul><ul><li>Particular task </li></ul></ul><ul><u...
Probabilistic mapping <ul><li>Activation Likelihood Estimate (ALE) </li></ul><ul><ul><li>BrainMap  </li></ul></ul><ul><ul>...
ALE method
Methods <ul><li>Meta-analysis: </li></ul><ul><ul><li>ALE analytic method (Turkeltaub et al., 2002) </li></ul></ul><ul><ul>...
Pain Meta-Analysis <ul><li>Contrasts: </li></ul><ul><ul><li>Pain - baseline </li></ul></ul><ul><ul><li>Pain - control (war...
Pain Meta-Analysis Summary <ul><li>122 total original studies </li></ul><ul><ul><ul><li>fMRI: 79 </li></ul></ul></ul><ul><...
Thresholded 3D probability map Duerden, Fu, Rainville, Duncan. IASP 2008
Results: All pain <ul><li>IC (R): 34, 12, 8 p = 0.23 </li></ul><ul><li>IC (L): -36, 4, 6 p = 0.21 </li></ul>BILATERAL IC B...
Other Applications ALE Method <ul><li>Comparison different types of pain </li></ul><ul><li>Cold pain vs heat pain </li></u...
Pain sensitivity and cortical thickness in Zen meditators Grant, Duerden, Courtemanche, Duncan, Rainville.  Emotion  2009 ...
Pain and meditation <ul><li>Hypnosis, attention, expectancy or placebo </li></ul><ul><li>Modulate experience of pain  </li...
Pain and meditation <ul><li>What the effects of meditation on pain perception? </li></ul><ul><li>Would differences be link...
<ul><li>Grant & Rainville. Psychosomatic Medicine 71:106–114 (2009) </li></ul>
Pain mask
Pain mask
Pain Meta-Analysis Zen meditators have thicker cortex in pain processing regions Grant, Duerden, Courtemanche, Duncan, and...
Pain and meditation <ul><li>Meditators required hotter temperatures  </li></ul><ul><li>Less pain while attending mindfully...
Other Applications ALE Method <ul><li>Comparison different types of pain </li></ul><ul><li>Cold pain vs heat pain </li></u...
Brain morphometric changes associated with pain catastrophizing D. Laverdure-Dupont; E.G. Duerden; A.-A. Dubé; K.J. Worsle...
Pain catastrophizing <ul><li>Personality trait </li></ul><ul><ul><li>Coping strategy </li></ul></ul><ul><li>Pain  </li></u...
Pain catastrophizing <ul><li>Personality traits are associated with cortical morphometric changes  </li></ul><ul><li>PC </...
Pain catastrophizing PCS is significantly correlated with CT in ACC
Pain catastrophizing <ul><li>PC is linked to morphometric differences  </li></ul><ul><li>Limbic-paralimbic system </li></u...
Outline <ul><li>Pain processing regions </li></ul><ul><ul><li>Meta-analysis </li></ul></ul><ul><ul><ul><li>Applications </...
Memory traces of pain in human cortex Albanese, Duerden, Rainville, Duncan. J Neurosci, 2007
Introduction <ul><li>Evidence - sensory information is transiently stored </li></ul><ul><ul><li>Sensory-specific cortical ...
Methods: Stimulation protocol encoding retention retrieval
Copyright ©2007 Society for Neuroscience Albanese, M.-C. et al. J. Neurosci. 2007;27:4612-4620 Figure 2. Cortical regions ...
Copyright ©2007 Society for Neuroscience Albanese, M.-C. et al. J. Neurosci. 2007;27:4612-4620 Figure 3. Mean time course ...
Conclusions   <ul><li>Sustained  pain-related activity </li></ul><ul><ul><li>SI associated with ISI in the MEMORY trials <...
Long-term memory <ul><li>Brain plasticity </li></ul><ul><ul><li>Training-related changes </li></ul></ul><ul><ul><li>Learni...
Copyright ©2008 Society for Neuroscience Duerden, E. G. et al. J. Neurosci. 2008;28:8655-8657 Figure 1. Meta-analysis of v...
Habituation to painful stimuli <ul><ul><li>ratings tested for habituation  </li></ul></ul><ul><ul><ul><li>sessions 1-4 </l...
Pain Stimulus Session 1-4: H
Copyright ©2004 Society for Neuroscience Apkarian, A. V. et al. J. Neurosci. 2004;24:10410-10415 Figure 2. Regional gray m...
Copyright ©2007 Society for Neuroscience Kuchinad, A. et al. J. Neurosci. 2007;27:4004-4007 Figure 2. Voxel-wise compariso...
DaSilva et al., Neurology. 2007 Nov 20;69(21):1990-5
Chronic pain <ul><li>Pain management </li></ul><ul><ul><li>Sensitive tests for measuring pain </li></ul></ul><ul><ul><li>B...
Training: phantom limb pain <ul><li>Correlation - cortical remapping and pain in the phantom-limb </li></ul><ul><li>Malada...
Acknowledgements   Mentors: Dr. Gary Duncan Dr. Pierre Rainville Funding Canadian Institutes of Health Research (CIHR)   L...
Thank you
Introduction <ul><li>These ‘maps’ are found in primary and secondary sensory areas and in thalamic nuclei </li></ul><ul><l...
Topographic maps <ul><li>There is a similar somatotopic map in the primary somatosensory cortex (S1) that is the main sens...
Phantom limbs <ul><li>Studies have shown that cortical representations surrounding those that are inactive due to the loss...
Why do a meta-analysis? <ul><ul><li>Contiguous activation </li></ul></ul><ul><ul><li>Particular task </li></ul></ul><ul><u...
Introduction <ul><li>What causes chronic pain ? </li></ul><ul><ul><li>Plasticity = sites throughout pain pathway </li></ul...
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  • Brain Health group Janet Muchison
  • The variable Xi is defined as the likelihood of a pain-evoked activation coordinate will occur in any voxel in the anatomical MRI. The value of d is calculated as the Euclidean (3D) distance between the centre of mass of the voxel and that of the coordinate. The value for σ is the standard deviation of the Gaussian blurring kernel. In the present study the standard deviation is 3.4mm with a FWHM blurring kernel of 8mm. This value was determined based on the average blurring kernel used by all of the studies included in the meta-analysis. Resulting values at each voxel are then multiplied by 8mm 3 (ΔV) to determine the extent of spatial localization probability of a pain-evoked activation occurring in the 3D template MRI that is sampled into 2 x 2 x 2mm voxels. For each coordinate in the meta-analysis the probabilistic value of pain-evoked activation is calculated and this value is also calculated for the coordinates as a whole.
  • We then performed a quantitative voxel-level meta-analysis on the coordinates and generated an ALE map. The method applies a spatial localization technique whereby each reported coordinate is initially given equal weighting not taking into account effect size. Probabilistic values are calculated for each coordinate whereby each point is assigned a likelihood of obtaining pain-evoked activation in every voxel in the template MRI. Values are assigned using the following formula from Laird et al., : The variable Xi is defined as the likelihood of a pain-evoked activation coordinate will occur in any voxel in the anatomical MRI. The value of d is calculated as the Euclidean (3D) distance between the centre of mass of the voxel and that of the coordinate. The value for σ is the standard deviation of the Gaussian blurring kernel. In the present study the standard deviation is 3.4mm with a FWHM blurring kernel of 8mm. This value was determined based on the average blurring kernel used by all of the studies included in the meta-analysis. Resulting values at each voxel are then multiplied by 8mm 3 (ΔV) to determine the extent of spatial localization probability of a pain-evoked activation occurring in the 3D template MRI that is sampled into 2 x 2 x 2mm voxels. For each coordinate in the meta-analysis the probabilistic value of pain-evoked activation is calculated and this value is also calculated for the coordinates as a whole. In order to determine the distribution of the resulting ALE values, the resulting maps were compared to those randomly generated by way of a non-parametric permutation test (N=5000) . Essentially, 5000 groups of the same number of coordinates as that used in the meta-analysis of randomly generated coordinates were created and tested according to the same methods. The resulting distribution is then used as the null hypothesis to which the ALE values computed for the pain-evoked activation is compared to. The permutation test essentially determines as to whether the pain-evoked activation could be generated by random coordinates alone or represents coherent activation pattern across studies.
  • MNI outside 112 Tal 43
  • Pronounced recruitment of affective processes in high catastrophizers appears to be associated with an enhanced development of areas associated with emotional processing
  • I am interested to study long term effects of repeated exposure to painful stimuli and its relation to brain plasticity Not only training related changes in the brain and the effects of learning - next slide is a meta analysis on training related changes But also some models of chronic pain have been linked to rely on similar mechanisms involved in memory formation - such as LTP Also interested in brain plasticity in relation to loss of input as in the case of amputation Using online training to modify maladaptive brain plasticity
  • Results demonstrate that although structural changes occur in functional areas related to the task, increases also occur in associative areas such as the posterior parietal and temporal cortices. Furthermore, studies examining explicit learning showed an overlap of increased gray matter density in the hippocampal gyrus.
  • orderly connections between peripheral nerve afferents and the CNS
  • Duerden Rotman 2009 07 29

    1. 1. Impacts of pain on brain health explored using neuroimaging techniques: implications for patient treatment Emma Duerden, M.Sc. PhD candidate (Neurological Sciences) Département de physiologie Université de Montréal
    2. 2. Outline <ul><li>Introduction </li></ul><ul><ul><li>background </li></ul></ul><ul><li>Pain processing regions </li></ul><ul><ul><li>Meta-analysis </li></ul></ul><ul><ul><ul><li>Applications </li></ul></ul></ul><ul><ul><ul><ul><li>ROI analysis </li></ul></ul></ul></ul><ul><ul><ul><ul><ul><li>Cortical thickness </li></ul></ul></ul></ul></ul><ul><ul><ul><ul><ul><li>Meditation </li></ul></ul></ul></ul></ul><ul><ul><ul><ul><ul><li>Pain catastrophizing </li></ul></ul></ul></ul></ul><ul><li>Pain and memory </li></ul><ul><ul><li>fMRI study: Short-term memory of pain </li></ul></ul><ul><li>Applications to patient treatment </li></ul><ul><ul><li>Brain-plasticity </li></ul></ul><ul><ul><li>Amputation - phantom-limb pain </li></ul></ul><ul><ul><li>Training </li></ul></ul>
    3. 3. Introduction <ul><li>Pain: </li></ul><ul><ul><li>Unpleasant sensory and emotional experience </li></ul></ul><ul><ul><li>Actual or potential tissue damage </li></ul></ul>
    4. 4. Introduction <ul><li>Pain: </li></ul><ul><li>Statistics Canada 2001 </li></ul><ul><ul><li>1.5 million persons aged 15 to 64 </li></ul></ul><ul><ul><li>3 in 4 persons </li></ul></ul><ul><ul><li>Women = 8.3% </li></ul></ul><ul><ul><li>Men = 6.7% </li></ul></ul><ul><ul><li>70% = affects daily life </li></ul></ul><ul><li>National Population Health Survey (NPHS) </li></ul><ul><ul><li>1/4 seniors at home </li></ul></ul><ul><ul><li>4/10 seniors in institutions </li></ul></ul>
    5. 5. Introduction <ul><li>Pain = psychological experience </li></ul><ul><li>No objective measures </li></ul><ul><li>Sensory and affective components of pain </li></ul>
    6. 6. Peripheral mechanisms of pain
    7. 7. Central mechanisms of pain
    8. 8. Introduction <ul><li>Neural processing of painful stimuli </li></ul><ul><li>Broad network of interconnected cortical regions </li></ul><ul><li>Sensory-discriminative </li></ul><ul><li>Emotional-motivational </li></ul>
    9. 9. Introduction <ul><li>Discriminative processing of pain </li></ul><ul><ul><li>Lateral pain system </li></ul></ul><ul><ul><ul><li>SI </li></ul></ul></ul><ul><ul><ul><li>secondary somatosensory cortex (SII) </li></ul></ul></ul><ul><ul><ul><li>Thalamus (ventroposterior lateral and medial nuclei) </li></ul></ul></ul>
    10. 10. Introduction <ul><li>Affective (unpleasantness) processing of pain </li></ul><ul><ul><li>Medial pain system </li></ul></ul><ul><ul><ul><li>ACC </li></ul></ul></ul><ul><ul><ul><li>PFC </li></ul></ul></ul>
    11. 11. Brain imaging methods Laboratory of Neuro Imaging (LONI) at UCLA (http://www.loni.ucla.edu/)
    12. 12. http://www.fmrib.ox.ac.uk
    13. 13. Brain activity during pain <ul><ul><li>Positron emission tomography </li></ul></ul>
    14. 14. Brain activity during pain
    15. 15. Brain activity during pain
    16. 16. Brain activity during pain Rainville et al. , M édecine Science 16 (2000) Thalamus S1 S2 Insula ACC
    17. 17. Why do a meta-analysis? <ul><ul><li>Contiguous activation </li></ul></ul><ul><ul><li>Particular task </li></ul></ul><ul><ul><li>Cognitive function </li></ul></ul><ul><ul><li>Particular function across different tasks </li></ul></ul><ul><ul><ul><li>e.g. working memory </li></ul></ul></ul><ul><ul><li>Problems with single fMRI/PET studies: </li></ul></ul><ul><ul><ul><li>Study confounds: </li></ul></ul></ul><ul><ul><ul><ul><li>Artifacts, head motion, few subjects, inter-individual variability, low SNR </li></ul></ul></ul></ul><ul><ul><ul><ul><li>Type I errors (5% false positives) </li></ul></ul></ul></ul><ul><ul><ul><ul><li>Greater rates of Type II error </li></ul></ul></ul></ul><ul><ul><ul><ul><li>Contamination from irrelevant task features </li></ul></ul></ul></ul>
    18. 18. Probabilistic mapping <ul><li>Activation Likelihood Estimate (ALE) </li></ul><ul><ul><li>BrainMap </li></ul></ul><ul><ul><li>GingerALE </li></ul></ul><ul><ul><ul><li>Convert coordinates = MNI and Talairach </li></ul></ul></ul><ul><ul><ul><li>Meta-Analysis </li></ul></ul></ul><ul><ul><ul><li>Group of coordinates </li></ul></ul></ul><ul><ul><ul><li>Comparison ALE meta-analysis 2 groups </li></ul></ul></ul><ul><ul><li>Method assessing statistical significance </li></ul></ul><ul><ul><ul><li>Test peaks distributed at multiple sites </li></ul></ul></ul><ul><ul><ul><li>Against H 0 of random distribution </li></ul></ul></ul>
    19. 19. ALE method
    20. 20. Methods <ul><li>Meta-analysis: </li></ul><ul><ul><li>ALE analytic method (Turkeltaub et al., 2002) </li></ul></ul><ul><ul><li>Talairach space </li></ul></ul><ul><ul><li>Date blurred (8mm) </li></ul></ul><ul><ul><li>Distribution determined through permutation test (N=5000) </li></ul></ul><ul><ul><li>Thresholded (p = 0.003) </li></ul></ul><ul><ul><ul><li>controlling the FDR q = 0.05 </li></ul></ul></ul><ul><ul><li>ALE maps displayed on anatomical MRI </li></ul></ul><ul><ul><li>Peak p values ABOVE threshold displayed </li></ul></ul>
    21. 21. Pain Meta-Analysis <ul><li>Contrasts: </li></ul><ul><ul><li>Pain - baseline </li></ul></ul><ul><ul><li>Pain - control (warm, cool) </li></ul></ul><ul><ul><li>High pain - low pain </li></ul></ul><ul><ul><li>Correlation PI/PU </li></ul></ul><ul><ul><li>Externally administered stimuli </li></ul></ul><ul><ul><li>Between groups (high vs low sensitivity; PET studies) </li></ul></ul>
    22. 22. Pain Meta-Analysis Summary <ul><li>122 total original studies </li></ul><ul><ul><ul><li>fMRI: 79 </li></ul></ul></ul><ul><ul><ul><li>PET: 43 </li></ul></ul></ul><ul><li>130 total </li></ul><ul><li>2699 points! </li></ul>
    23. 23. Thresholded 3D probability map Duerden, Fu, Rainville, Duncan. IASP 2008
    24. 24. Results: All pain <ul><li>IC (R): 34, 12, 8 p = 0.23 </li></ul><ul><li>IC (L): -36, 4, 6 p = 0.21 </li></ul>BILATERAL IC BILATERAL thalamus BILATERAL SII R: 52, -26, 22 p = 0.18 L: -52, -24, 22 p = 0.17 0.25 0.003 THAL (R): 10, -18, 6 p = 0.22 THAL (L): -14, -16, 8 p = 0.25
    25. 25. Other Applications ALE Method <ul><li>Comparison different types of pain </li></ul><ul><li>Cold pain vs heat pain </li></ul><ul><li>Left vs right </li></ul><ul><li>fMRI vs PET </li></ul><ul><li>ROI analysis: </li></ul><ul><ul><li>Cortical thickness </li></ul></ul>
    26. 26. Pain sensitivity and cortical thickness in Zen meditators Grant, Duerden, Courtemanche, Duncan, Rainville. Emotion 2009 submitted
    27. 27. Pain and meditation <ul><li>Hypnosis, attention, expectancy or placebo </li></ul><ul><li>Modulate experience of pain </li></ul><ul><li>Mindfulness meditation </li></ul><ul><ul><li>Effective in treating chronic pain </li></ul></ul><ul><ul><li>Emotional and functional </li></ul></ul><ul><ul><li>No long-term effects on pain sensation </li></ul></ul>
    28. 28. Pain and meditation <ul><li>What the effects of meditation on pain perception? </li></ul><ul><li>Would differences be linked to morphological changes in the brain? </li></ul>
    29. 29. <ul><li>Grant & Rainville. Psychosomatic Medicine 71:106–114 (2009) </li></ul>
    30. 30. Pain mask
    31. 31. Pain mask
    32. 32. Pain Meta-Analysis Zen meditators have thicker cortex in pain processing regions Grant, Duerden, Courtemanche, Duncan, and Rainville, Emotion 2009 submitted
    33. 33. Pain and meditation <ul><li>Meditators required hotter temperatures </li></ul><ul><li>Less pain while attending mindfully </li></ul><ul><li>Correlation with increased thickness in pain regions </li></ul><ul><li>Greater ability to modulate pain </li></ul>
    34. 34. Other Applications ALE Method <ul><li>Comparison different types of pain </li></ul><ul><li>Cold pain vs heat pain </li></ul><ul><li>Left vs right </li></ul><ul><li>fMRI vs PET </li></ul><ul><li>ROI analysis: </li></ul><ul><ul><li>Cortical thickness </li></ul></ul>
    35. 35. Brain morphometric changes associated with pain catastrophizing D. Laverdure-Dupont; E.G. Duerden; A.-A. Dubé; K.J. Worsley; G.H. Duncan; G. Lavigne; P. Rainville
    36. 36. Pain catastrophizing <ul><li>Personality trait </li></ul><ul><ul><li>Coping strategy </li></ul></ul><ul><li>Pain </li></ul><ul><ul><li>Awful, horrible and unbearable </li></ul></ul><ul><ul><li>Augments pain perception </li></ul></ul><ul><ul><ul><li>enhanced attention to painful stimuli </li></ul></ul></ul><ul><ul><ul><li>heightened emotional responses to pain </li></ul></ul></ul>
    37. 37. Pain catastrophizing <ul><li>Personality traits are associated with cortical morphometric changes </li></ul><ul><li>PC </li></ul><ul><ul><li>ACC PFC in chronic pain patients </li></ul></ul><ul><li>CT analysis </li></ul><ul><li>Identify potential persistent neural substrates underlying PC </li></ul><ul><li>20 young, healthy, subjects (RH; Age=23.2yrs; M=11). </li></ul>
    38. 38. Pain catastrophizing PCS is significantly correlated with CT in ACC
    39. 39. Pain catastrophizing <ul><li>PC is linked to morphometric differences </li></ul><ul><li>Limbic-paralimbic system </li></ul><ul><li>Pronounced recruitment of affective processes in high catastrophizers </li></ul><ul><li>Enhanced development </li></ul><ul><li>Emotional processing brain regions </li></ul>
    40. 40. Outline <ul><li>Pain processing regions </li></ul><ul><ul><li>Meta-analysis </li></ul></ul><ul><ul><ul><li>Applications </li></ul></ul></ul><ul><ul><ul><ul><li>ROI analysis </li></ul></ul></ul></ul><ul><ul><ul><ul><ul><li>Cortical thickness </li></ul></ul></ul></ul></ul><ul><ul><ul><ul><ul><li>Pain catastrophizing </li></ul></ul></ul></ul></ul><ul><li>Pain and memory </li></ul><ul><ul><li>fMRI study: Short-term memory of pain </li></ul></ul><ul><li>Applications to patient treatment </li></ul><ul><ul><li>Brain-plasticity </li></ul></ul><ul><ul><li>Amputation - phantom-limb pain </li></ul></ul><ul><ul><li>Training </li></ul></ul>
    41. 41. Memory traces of pain in human cortex Albanese, Duerden, Rainville, Duncan. J Neurosci, 2007
    42. 42. Introduction <ul><li>Evidence - sensory information is transiently stored </li></ul><ul><ul><li>Sensory-specific cortical areas </li></ul></ul><ul><ul><li>Involved in initial encoding </li></ul></ul><ul><ul><li>SI - transient storage site for tactile information </li></ul></ul><ul><ul><li>Noxious sensory information? </li></ul></ul><ul><li>Neural basis of encoding and retention </li></ul><ul><ul><li>Heat pain stimuli </li></ul></ul><ul><ul><li>Right palm in 8 healthy volunteers </li></ul></ul>
    43. 43. Methods: Stimulation protocol encoding retention retrieval
    44. 44. Copyright ©2007 Society for Neuroscience Albanese, M.-C. et al. J. Neurosci. 2007;27:4612-4620 Figure 2. Cortical regions significantly activated during the ISI between the pairs of stimuli in both the memory and control trials and memory-specific activation observed within pain-related sites
    45. 45. Copyright ©2007 Society for Neuroscience Albanese, M.-C. et al. J. Neurosci. 2007;27:4612-4620 Figure 3. Mean time course of the memory-specific percentage BOLD signal from the group average observed during the course of experimental and control trials, synchronized on the start of each trial
    46. 46. Conclusions <ul><li>Sustained pain-related activity </li></ul><ul><ul><li>SI associated with ISI in the MEMORY trials </li></ul></ul><ul><li>Suggests a short-term retention of a 'pain trace’ </li></ul><ul><li>Sensory-specific cortex </li></ul>
    47. 47. Long-term memory <ul><li>Brain plasticity </li></ul><ul><ul><li>Training-related changes </li></ul></ul><ul><ul><li>Learning </li></ul></ul><ul><ul><li>Chronic pain </li></ul></ul>
    48. 48. Copyright ©2008 Society for Neuroscience Duerden, E. G. et al. J. Neurosci. 2008;28:8655-8657 Figure 1. Meta-analysis of voxel-based morphometric studies reporting increased gray matter density after learning in the cortex and cerebellum
    49. 49. Habituation to painful stimuli <ul><ul><li>ratings tested for habituation </li></ul></ul><ul><ul><ul><li>sessions 1-4 </li></ul></ul></ul>* * * *
    50. 50. Pain Stimulus Session 1-4: H
    51. 51. Copyright ©2004 Society for Neuroscience Apkarian, A. V. et al. J. Neurosci. 2004;24:10410-10415 Figure 2. Regional gray matter density decreases in CBP subjects
    52. 52. Copyright ©2007 Society for Neuroscience Kuchinad, A. et al. J. Neurosci. 2007;27:4004-4007 Figure 2. Voxel-wise comparison of gray matter density between fibromyalgia patients and healthy control subjects
    53. 53. DaSilva et al., Neurology. 2007 Nov 20;69(21):1990-5
    54. 54. Chronic pain <ul><li>Pain management </li></ul><ul><ul><li>Sensitive tests for measuring pain </li></ul></ul><ul><ul><li>Brain imaging? </li></ul></ul><ul><li>Pain treatment </li></ul><ul><ul><li>Mindfulness </li></ul></ul><ul><ul><li>Hypnosis </li></ul></ul><ul><ul><li>Training </li></ul></ul>
    55. 55. Training: phantom limb pain <ul><li>Correlation - cortical remapping and pain in the phantom-limb </li></ul><ul><li>Maladaptive mapping </li></ul><ul><ul><li>Reversed </li></ul></ul><ul><ul><li>Sensory training paradigms </li></ul></ul><ul><li>Post-training =  pain and cortical reorganization </li></ul>(Flor et al. 2001)
    56. 56. Acknowledgements Mentors: Dr. Gary Duncan Dr. Pierre Rainville Funding Canadian Institutes of Health Research (CIHR) Lab mates: Dr. Marie-Claire Albanese Jen-I Chen Mathieu Roy Joshua Grant Audrey-Anne Dub é Marianne Arsenault Mathieu Piché Collaborators: Dr. Bruce Pike Dr. Stefan Posse Dr. Keith Worsley Tech Support: Mathieu Desrosiers Leo Tenbokum
    57. 57. Thank you
    58. 58. Introduction <ul><li>These ‘maps’ are found in primary and secondary sensory areas and in thalamic nuclei </li></ul><ul><li>Many sensory systems are characterized by cortical representations of surface receptors, whereby the occurrence of neighbouring inputs is preserved in the cortex </li></ul>
    59. 59. Topographic maps <ul><li>There is a similar somatotopic map in the primary somatosensory cortex (S1) that is the main sensory receptive area for the sense of touch </li></ul><ul><li>Areas of skin that are highly innervated and that have fine sensory discriminative properties have a larger cortical representation </li></ul>Primary somatosensory cortex
    60. 60. Phantom limbs <ul><li>Studies have shown that cortical representations surrounding those that are inactive due to the loss of the limb will encroach on that region </li></ul><ul><li>Pain in the amputated body part occurs in 50–80% of all amputees </li></ul><ul><li>Cortical remapping as a result of an amputation often results in painful sensations in the amputated limb so called “ phantom limb” pain </li></ul>
    61. 61. Why do a meta-analysis? <ul><ul><li>Contiguous activation </li></ul></ul><ul><ul><li>Particular task </li></ul></ul><ul><ul><li>Cognitive function </li></ul></ul><ul><ul><li>Particular function across different tasks </li></ul></ul><ul><ul><ul><li>e.g. working memory </li></ul></ul></ul><ul><ul><li>Problems with single fMRI/PET studies: </li></ul></ul><ul><ul><ul><li>Study confounds: </li></ul></ul></ul><ul><ul><ul><ul><li>Artifacts, head motion, few subjects, inter-individual variability, low SNR </li></ul></ul></ul></ul><ul><ul><ul><ul><li>Type I errors (5% false positives) </li></ul></ul></ul></ul><ul><ul><ul><ul><li>Greater rates of Type II error </li></ul></ul></ul></ul><ul><ul><ul><ul><li>Contamination from irrelevant task features </li></ul></ul></ul></ul><ul><ul><ul><ul><li>Assumptions made based on Task A - B </li></ul></ul></ul></ul><ul><ul><ul><ul><li>Each task isolates process? </li></ul></ul></ul></ul>
    62. 62. Introduction <ul><li>What causes chronic pain ? </li></ul><ul><ul><li>Plasticity = sites throughout pain pathway </li></ul></ul><ul><ul><li>Changes in peripheral receptors </li></ul></ul><ul><ul><ul><li>receptor </li></ul></ul></ul><ul><ul><ul><ul><li>channel expression </li></ul></ul></ul></ul><ul><ul><ul><ul><li>Distribution </li></ul></ul></ul></ul><ul><ul><ul><ul><li>activation threshold </li></ul></ul></ul></ul><ul><ul><li>Strengthening synapses </li></ul></ul><ul><ul><li>LTP = DHN </li></ul></ul>
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